Machine learning powered ellipsometry  被引量:4

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作  者:Jinchao Liu Di Zhang Dianqiang Yu Mengxin Ren Jingjun Xu 

机构地区:[1]The Key Laboratory of Weak-Light Nonlinear Photonics,Ministry of Education,School of Physics and TEDA Applied Physics Institute,Nankai University,Tianjin 300071,China [2]College of Artificial Intelligence,Nankai University,Tianjin 300071,China [3]Collabo rative Innovation Center of Extreme Optics,Shanxi University,Taiyuan,Shanxi 030006,China

出  处:《Light(Science & Applications)》2021年第4期582-588,共7页光(科学与应用)(英文版)

基  金:the National Key R&D Program of China(2017YFA0305100,2017YFA0303800,and 2019YFA0705000);National Natural Science Foundation of China(92050114,62076140,91750204,61775106,11904182,61633012,11711530205,11374006,12074200,and 11774185);Guangdong Major Project of Basic and Applied Basic Research(2020B0301030009);111 Projea(B07013);PCSIRT(IRT0149);Open Research Program of Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province;Tianjin Youth Talent Support Program;Fundamental Research Funds for the Central Universities(010-63201003,010-63201008,and 010-63201009);。

摘  要:Ellipsometry is a powerful method for determining both the optical constants and thickness of thin films.For decades,solutions to ill-posed inverse ellipsometric problems require substantial human-expert intervention and have become essentially human-in-the-loop trial-and-error processes that are not only tedious and time-consuming but also limit the applicability of ellipsometry.Here,we demonstrate a machine learning based approach for solving ellipsometric problems in an unambiguous and fully automatic manner while showing superior performance.The proposed approach is experimentally validated by using a broad range of films covering categories of metals,semiconductors,and dielectrics.This method is compatible with existing ellipsometers and paves the way for realizing the automatic,rapid,high-throughput optical characterization of films.

关 键 词:consuming INVERSE essentially 

分 类 号:TP181[自动化与计算机技术—控制理论与控制工程]

 

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